{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 单变量房价预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set(context=\"notebook\", style=\"whitegrid\", palette=\"dark\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x22271e0eca0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df0 = pd.read_csv('data0.csv', names=['square', 'price'])\n",
    "sns.lmplot('square', 'price', df0, height=8, fit_reg=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype\n",
      "---  ------  --------------  -----\n",
      " 0   square  47 non-null     int64\n",
      " 1   price   47 non-null     int64\n",
      "dtypes: int64(2)\n",
      "memory usage: 880.0 bytes\n"
     ]
    }
   ],
   "source": [
    "df0.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 多变量房价预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2104</td>\n",
       "      <td>3</td>\n",
       "      <td>399900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1600</td>\n",
       "      <td>3</td>\n",
       "      <td>329900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2400</td>\n",
       "      <td>3</td>\n",
       "      <td>369000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1416</td>\n",
       "      <td>2</td>\n",
       "      <td>232000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3000</td>\n",
       "      <td>4</td>\n",
       "      <td>539900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   square  bedrooms   price\n",
       "0    2104         3  399900\n",
       "1    1600         3  329900\n",
       "2    2400         3  369000\n",
       "3    1416         2  232000\n",
       "4    3000         4  539900"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from mpl_toolkits import mplot3d\n",
    "\n",
    "df1 = pd.read_csv('data1.csv', names=['square', 'bedrooms', 'price'])\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x22272b9d640>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "# 创建一个 Axes3D object\n",
    "ax = plt.axes(projection='3d')\n",
    "# 设置 3 个坐标轴的名称\n",
    "ax.set_xlabel('square')\n",
    "ax.set_ylabel('bedrooms')\n",
    "ax.set_zlabel('price')\n",
    "# 绘制 3D 散点图\n",
    "ax.scatter3D(df1['square'], df1['bedrooms'], df1['price'], c=df1['price'], cmap='Greens')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据规范化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.130010</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.475747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.504190</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>-0.084074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.502476</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.228626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.735723</td>\n",
       "      <td>-1.537767</td>\n",
       "      <td>-0.867025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.257476</td>\n",
       "      <td>1.090417</td>\n",
       "      <td>1.595389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     square  bedrooms     price\n",
       "0  0.130010 -0.223675  0.475747\n",
       "1 -0.504190 -0.223675 -0.084074\n",
       "2  0.502476 -0.223675  0.228626\n",
       "3 -0.735723 -1.537767 -0.867025\n",
       "4  1.257476  1.090417  1.595389"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def normalize_feature(df):\n",
    "    return df.apply(lambda column: (column - column.mean()) / column.std())\n",
    "\n",
    "df = normalize_feature(df1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x22271e4d070>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h3VHepLPyAOjkQ2CXtdmnOtjJuNMk4HFhUjrd1dM3Y/X0zbh06dJQ++ek6+Wx33fffbjvvvs82x5wg5GuE9nyi1uWZSvqzeVyVvdYp7ynE7xIDQDDR8z82AuFAmRZHphsOaYp0p12TW0/6CRrs49lF4dPSpKEvb29No3xODCr6Q3TNGdiKsUNQbrdGho4GGMoFovY2dnB4uLi0ITFCdOtgmEQ0hMfFIuLi1hfX0epVHIle5oW0p0UxkE8nUbsFItF1Go1hMNhR1mbk8bYK0zSy5dj2PtnlJ4RXuJQk24/DQ2qqiKbzaJSqSAajToOehwEXuls+9mGOBF4cXHROnZuGDIshol0J32jHibwAl4ikbB+5yRrK5fLUFW1zSqxl29tN4jOeJMAl2u6iXSnHYeOdPtpaAAARVGQzWZRq9WwvLyM5eVl62J3g3G4hIlk6zQReFTWjj7GA6cHmJOsjb+Wu3N1krWJZNxL1jZp3wU3pO9HumNGPw0NQNPIJZvNotFoYGVlBZubm5Bl2bMurFF2lOm6jmw2axnodIrK3R7DsKQ7qmh3Eg+ASUbug+x7GFlbMBh0JGMv6hFu4Yb0TdP0SXcc6LehgXeP6bqOVCqFra2tli9XkiTXjQ18O16nF0S3smQy2dNAx4tId9DX+9Gxd/DaRFwEn3XmJGvjxTp+v4TD4bEbBLkhXa9bgEeF6T/CDuBkWygUIEmS1ajQqXuMMYZUKoXFxUXHi8huyzgsvEwvaJqGbDaLcrncF9mK7z8s6YVZiDZnad/irDMR/HqrVqtoNBotsrZOo5ZGcYxuSdePdEcA+zicer2OQCDQNiyPTzqQZRnpdBrz8/NdLxKvGhu82A5XUuzu7g5sDQl4PzmiG7jROZep2X0KZqGwMW1gjI39c+OyNq7xPnLkCIB2WVu1WoWmaWCMuZp71wl+pDuF4O26vKEhEAhYaQFx0gEfmBiPx/t6InOdrlu4IV1RSRGLxQYmW/EYRh3p8gcDH+GTSqWsG1ScCCvmD/nPLHjaThLTFGV3krWJo5Y6zb0bRtbmRoHgR7ojAp93L/6bk5WbSQeTjHRFsl1eXkYymbQq1cNglOkFcRURDAat4ZQ8+rH7VfD8odiJRSlti5C8iJK8xDQR3zjRb6TZz9w77tZmnwDcbSXkpxemHIZhoFqtolqtYmFhoc2icBBMopDWaDSQzWZRrVZbTM8zmcxEc7JO7+f58UwmA1mWsbGx0eZTYUen/CHXm/Ila6VSgaZpkCSpLSr2wkRo1jDJ83Xrbtdr7p19JWSXtfFoeRj46oURQtSp8qXP0aNHXW3Ty0JaL/K2k+3GxkbLxSJJkiv5GifNYW8gkXQZY6hUKtjb24MkSVhbW2tzVxsUnTxtud5UVdWWG5Mxhp2dnRZCnuYUhVGugBk6AsmkKwKbBEah0+1mECSuhKrVqjWItNFodJS1OWFUXrqjwPQfoQ26ruPJJ5+0dKq6rmNnZ8f1dr00q+lEmI1GA5lMBrVaDSsrK21ky+FFpOpGc8kLcZxsAWB1dbVnMdINxChJjKB1XcelS5cQj8etFIV97I6XhRyOYT47xhiu/Pknkf9v/wCAYO725+DEu98JuceKwIt9e4Vx7lskY14Iz2azlhqpk6zNTsaBQMBzh7FRYvqP0IZQKNQye4xrdN2CE5XbvJBTeoF3v9XrdaysrODIkSNdo4lJDqdkjKFWq4Exht3dXaTTacukfRT76wVuYLKwsNDyezFFwQs59pZYkZDHQSSFr38Dub9/GMFkEpAkVH/yKK7+1d9g63/5w4G2Mws53VHun9tgdpK1cTLmNYLvfOc7+PSnP4319XU897nPxenTp/GSl7wEm5v9T52w4+Mf/zjOnDkDoGnx+MADD7g6LxEzR7qEkBZS9CotIG7LK9JVFAWZTAaKovRFtk7bGBbDkGCtVsPe3p5lDHTTTTdN7RK+U4qC5w75clVUUdij4m4pimEeIPWz50AkCeTg+pHicdR+/tjA27lRIl0ndCP9Tm5t6XQaoVAIjz32GK5evYpvfetbePTRR/H+979/qGN45JFH8O1vfxtf+tKXQAjBvffei6997Wt4xSteMdT27Jg50gVaCcUrqRfgXTeZruu4fPkyFEVBKpXC0aNHB4oevIgaBzmXer2Ovb09aJqGdDqNxcVFPPbY4GQxaYjLVTFF4RQhOaUo7PKmQckncmQTzDQt4qKKgsjRIwOfx6QjXbf+I273P2ikPTc3h7vuugvPfe5zcccdd7j+7FKpFN7xjndYOejt7W1cu3bN1TZFzCTpiuAfsBfLIrcEXq/Xkclk0Gg0sLa2NjDZcowr0lUUBXt7e1BVFalUCkmh8DMNffgcXjyAOvnZ8vSE3bUrEAhA13WUy+W+UxTLr341St/9HqqP/gxEkhBKpbD5tt8b+Hj9SHeyXrqnTp2y/n7p0iWcOXPGGtnjBQ4F6XLFgFvSHZbsONmqqorFxUVQSrG8vDz0cbjtKOPb6ERWjUYDe3t7ViRu96Ho9f5xYpQE0C1FUalUUCqVUK1Wkc/nW0budEpRSOEQtt//XtTPPwlmGIhun4TcY9qIEyYd6U46pzusl67Xx33+/Hm89a1vxQMPPIDjx497tt2ZJF07IUzKN6FWqyGTyUDTNKRSKSQSCSs6cnsco0gvcPUEL+h1i8SnhXTHDZ6iiEajqNfr2NjYANA9RWFv8oicuslVXcCPdCdvYP7DH/4Q999/P975znd6MhdNxEySrh1e5XX73Q53LONkKy7Lx2li3g0iaaqqikwmg2q12ndB70Yl3U7olKLo1oFlj4r7VVHcyJHusCtWLxsjdnZ28Pa3vx0PPfQQ7rzzTk+2KWImSdd+QY7DN4FLqTKZDAzDsCJb+7GMw8S8321omoZisWi1F3fSBXfCjUy6/RJfp3ZYu5etU4pCnH1md8e7ESNdN1MjvIx0/+qv/gqqquJP//RPrd/dc889eNOb3uTJ9meSdO3wsoXXvp1+yVbchtsmC7fpBR557ezstLQXD4JBI91R3qizRv7dvGxFkxg+iNKeouDXzyQwyUiX3zOTjnQffPBBPPjgg55sywkzSbpOka4XOV0xYuZGzplMBpTSrl689mNzW/kfNloWJ0twS8ulpaWhjmFa0guTjLoGen2jgdr/8zloP/kx5GQS8f/pdxA4cbLlNd1SFOLsM9M08fTTT7ekKESTmFE/4GYxtUEpbWummFbMJOna4WV6gRuwcLLttyPLvh03F9Cg3gmGYSCbzVoz006dOoWdnR3XE4lvdAzyGVQ//SlojzwCkliEceUKyh/8Uyy+7wOQ+1Cx2GefVatVHD9+HJRSKyquVCpQVbWtFVZ0aPPiO5tkpHsjOIwBPulaYIxZ7aT1en0osuXwYkZZP9GyffS6ODNtEtMjJl35nhQYpdC+912Q1EqzIy0cBs3lYDx5vi/SbdvegYk5d+ASDfo5EfM0Ra1WazEVtyspBiWxWY50fdIdIZyKV5qmDbUt7qKVyWRgmiaCwSC2t7ddm954pWBwughN00Qul0OhUMDCwgK2t7fb8oeTGk55WDDQuRMCEgoDug6EwwfvZSC278QLSJLUZirOp6mIKQquohCtE/lPN7cuP9IdPWaSdO0YJqcrzk8Dmv3bhBDkcjnXT/pRdZSZpol8Po98Po/5+XmcPHmyYx5rEpHurIPVa2Df+zZQKUPa3AJZ66+FlxCC2H/4bVQ/9VfAAeEGt08h+JzbBj+GISw5Cek8nl20TrS7dTlFxbMc6c6Cw1ipVJpN0nUjGRPNuCVJapmfxr083cJrrS6lFIVCAdlsFnNzc13JlmPcpMvJYlQYNRmwhgL6Fx9D6Uc/Rv6Jp0EpRfTu1wAPvruv90d+5aWQ02no55+AtLCI8IvvBHHhYeDFuTpZJwLOKQpVVa3/5yOYOCGPK/IdlnS51GyaSVfTNPzzP/8zzpw5M5uka0c/pMsYQ6lUsvw6ncy4p2k4JSHEmoyRzWYRi8Vw4sSJvidjuNX69ku6fHwPT8+Iy1h+485EQe/Jcyj/+Ke49sOzYJQCDND+699i/8W/iMT/8O/72kTw9C0Inr7F1WGMI9LslKLQNA1PP/00AoEAFEWxrBMHTVEMCzcaXWA6vXT5OX3lK1/Bz3/+czz++OOHg3S76XQ52WYyGQQCga6TD6aFdCmloJTi6aefRiwWw7Fjx9oGA/ZzDG6i9l6kK06U4ON7CCHWcrZer6NYLLbZKoqTH6YKlKL41BUwSiHJMhgYmG6i+Ldf7Jt0vcCklveEENCdHQQ/8hFo5TLCt92G9B/8AUgsZo3Z6ZSisHtRDAs3ZjcApjKny++hRx55BL/7u7+LdDo9m6Tbj05XHKAYCAT6mgw86YnAYtTI5WrDGueMMr1QrVaxt7cHxpj1EONDKEOhUEte0d4QwJeyhBDHqHhi6ocTN0EKhcAYBWMSwCjYgRJhnJgU6dJKBcX/9J9AikXQWAy1r30NRiaDlQ9+0Pp+nFIUYtcd/16d7DL7IdPDGOlyGIYBWZaxu7s7m6QLdPbUFYlr0DHsg+pjO2FQ0hWjcT5hN5vNtikSBsEoSFe0glxdXe2rWcSpIUCch+Y0st1OxuMAmV9A6v98N6p/+Edgmg4mESAWQ/ret4xl/xyTIl3t8cdB63UgHgcJBiEFg9AefRSsWgURyJajU4pC9KKo1+stKQp74c6eojBNc6hrnt9r0xjp8mN61atehTNnzuBb3/rW7JKuCE4Q+XweuVwOoVDIGg0+6Hb4stzNU7Nf0hWLevYJu/l83nVO1qucrqqq2NvbQ71e72gFOei2+Tw0EZ2iYgC4cuUKIpHI4FGxrgOGDkSiQI/Xx3/5V7D9uf8b+S98EVpDRfDXXonY7YMrENxgYumFUAigFIQ/aPmfAxQDxe/VrqKwpyhUVbVIln+nmqYNRbqmaVra9mnFa17zGiiKgtOnT88u6XJSoJRif38fQFOOMQzZivCipbhXPlXUBhNCRlLUc+vfwAt5V69eRblcHmjc0LDoFBWfP38eiUSizTzGvoy1D6YkZ38M6d/+ezNVkFoHfdlrgWj3ayN66y04cuu7sL+/j0ajMbJzdYJRKEK5eBEIjD9iCz372ZC3t0HPngVVVYAQzL3hDZD6LNx2g5hKElMUpmm2PGS5U1uhUGiLirulKGZh9LqqqlhaWsJDDz00u6RLKUU+n0c2m0UkEkEgEMDm5qbr5aiXI3vs4H4OfMKuKFezY5I6W8MwrOr1sIY5XoFHMPF4vGNOkc9DE3PFseo+Ev/yj6DJFORQCCS7C+m7Xwf91V8faN/jQunhM7j6jncBARlMN7D/gfchcbe3Pq7dQIJBzP3n/4z9v/s7xOt1hJ7zHERf9rKR7lOW5ZYUhaZpWFpaQigUaklR8IIsT1HYC3ezQLp//ud/jscffxy/9Eu/NLuke/XqVRiGga2tLcRiMVy4cGFkTmPDbEMkbu5Utre317efw7g7ypimgT7xU5TzOeTCc8ByGisrK1hdXR36GEaJbjlFVVXBdi83/95QQOs1yJAQvHge9X9XdIyKJwmjUMTVd7wLTIisr73z3Zj7xTsRWB7OsGgYsGAQgbvuQmJ9fWz7FMG7yrqlKMSx7Kqq4kMf+hDOnj2LY8eO4XnPex6e9axn4e6773YVfFWrVdxzzz345Cc/iSNHBp9x54SvfvWrePjhh5uNLJ5scQI4cuRI2/QIr4zMvWxsECfs8qGP/Rb13KYX+n0/bShofOqjMK89jbAs40Q0huIr/kcgkRh6/5OAmFMkaxuQolFEFxfBAJj7BejJFcvQSNM0SJLUlp7gxZ1xduPpV6+CBAIQ90gCAWhXroyXdKd4aoSYohDx7ne/G9/4xjdw+fJlXLp0Cd/85jdx/PhxvOAFLxjqGH7yk5/gwQcfxKVLl4Z6vxMURbG8NIAZbgO2R6Reeup6lV64ePGiNWG3mwdvp22MOr3AlR7V73wLy7tXENncakZ/tQpij/wzar9570D7myawjWNgN98Ocv6nIJKEQDgK8quvxWqiKcGzt8hWKhXkcjkrV8zTGvV6feRRcXBzE+xg7L11/IaBkEdRVr+Y9NSIYfa/vr6Ol7/85ZAkCTfddJPrY/j85z+P97znPcKkGWMAACAASURBVHjggQdcb4uDEIIXv/jFeOCBB/Cyl71sdkl3HJ66w0BRFGsi8Pr6esson0HQKS/cL7qRrl01sT4/h3A0CnBiCYVBlPpUeS8MfCySBHrnvwdOPxcwNGBxGQhfLwp1apHlxZ1isQhN05DL5awJwZ2iYrcILCWx8YH34tr/8W4rp7vx/v881igXmO5It9f7vBob//73v9+T7YiIRCK4//778cEPfhBf+MIXZpd07Zh0Y4M4YTeRSIBSOrSBOOBNIc3pPJwaGxALgT3yNUCpNyVCpQKM088bLekaOvDf/hbkR98FgkGwV70OeNEvdzyXoUAIsJQa6C28uKMoCoLBIFKplKNxDJc8OTV4DBMVJ177GszdeSf2n3gCyvwcEs95zsDbcItJT40YlvTdSjxHBa5QOnr0KDKZDP7kT/5k9psjRHhJuoNsx2nCrlcTgb2UjNXrdezt7UHXdayurrYW8taOgL3hzcA/fwVoKMDzfwnqbS8eLel+/WGQ7/13YDEJUBPk7/4rWGIJuPnZo9vnkOgWFYvGMZyMh42KA8tLCD/n2dAqlVGfkiO4j+8kwAl/GNKdVlvHZ555Bj/96U+xsLCAj370o1hYWGjOxJv0gXkFN566ImRZ7mtZb5+wu7m5aX3x0zARmEfK4kMhnU53THdIN90K3HTr9ffncmAefJ4dj+/xR4H4XDOlIcuAJAFPPj6VpNsJsiwjFot1HErZKyp2cvCatLWiV8v0YfZ92Lx019fXsbKygkKhgK2tLZw+fRr7+/uHh3S9yun2IjtN05DJZLpO2B2Vn+4gMAwDhmHg4sWLQzU2jPzGn18ACrnreVZKgbnF7u9hDHjiZyCXLzSj4ue9GAh6bxTe3NVw5NcrKraPahe1p+Fw2FUe3y0mTfiHzUs3mUwCAP71X/8VJ06cwG/8xm8AmGH1wrjTC+LQx6Wlpa4NA15NBB6GuMV5aYyxoRsb3ErWeoHd9UaQv/i/gP0iAAak1oEX/lL3Y/qXfwL5xy82/84Y2I+/B/Yf/wiYwhvOjn6i4lKpBEVRLPOgXlGx15jFqRG8K9XrSPcb3/iG623wpo16vY7vfve7uO2225oNHR4c31RgVDpdXdeRy+Wwv7+PZDKJU6dO9Xyq9jvjrBsGJV1xhM/i4iK2t7dx/vz5oS/GYaO8vrF+BOz+B4GnzgGBYDOtEOlsX8kMA+RrfwfE5wE5ADAG8vRTYBefAE7d2vF9w2Icyg2nqLhYLEJVVSwsLPSMinlHllfR6SQjXdM0hyZdYDrNbvhnGQqFsLOzg7/8y7/E2tra7JKu05w0L9UL4tDHRCLRMvRxkO24nQjcC+JUifn5eWteGq8Gu1kmj5x4EkvAHXf2dSygJmBSQJL5L5tOYPoI884TICDGWMeoWPQp2N/fb3beeTSQEph8pDsMcRoH+uZpTC/wz/L5z38+zp49i+985zv4t3/7t9klXaDd3tGr5bCqqjh//nzbhN1B4IX6oNv7GWMoFovIZDKIRqNtUyXcRtvDkO5II6VgCOxZt4Gc+ykQiwNaAyQUBts6OZr9TQidPsNOHVmilaLbqHgWc7rT7KXLP89nnnkG1WoVN910U1PeNukD8wo8veBG68etIRljOHXqlCs/Wy/UB07v540Ne3t7CAaDlvdEp20MG60O895R37Dst/5n4OHPAxceB1Y3wH79PwBzC6PZ14TkU4Nev3wg5aBRsZN716QjXTekO43pBR69/8Vf/AVe+9rX4p577gEww4U0O/iFOuhFa5omCoUCcrkc5ufncfz4cVy+fNkV4QLe62ztDmXr6+sdxw5xjJN0a7UayuXyaKdARKJNPfEhhhdk3y0q5kTsNE6Ju8txn4BxRr1uRvVwH+xpAz+m1dVV3Hnn9TTaTJOuSAyiAXm/o0E42cbjcWvCLqXUVcTM4WV6oWtjQxe4USD0S7qKomB3dxe6rmNubq7F77YfXWq/6HosugrSqAOyDBad72lWPs0Y5RK/05h2HhVXq1VUKhXk8/meUbHXGFYjPGm/iH6gaRre+9734rWvfS1WV1dnm3Tt4CmGbl8epRTFYtGasHv8+PGWXCjvipk06fJjuHz5MhqNBlKp1MA+Dm5Mc3qRrqZp2NvbQ61Wswx9dF23jo97GDQajZZco9dDKolSgXzp54BpgDAGM7EKeuSUa+KdVH5z3PsVo+JMJoONjQ0reOkWFduN490es5tIdxpTC8D11ffNN9+M73//+zhz5gwYY7NNuoOY3vDCEzc97zZh163yQNzGMOANGAAQi8Vw9OjRoY5lFOkFUQe8tLRkNYfYX2s3qAYApipgTzwKc6eE2sIKCgupFuNxcRyP2Dbb7YaWr10AiATEFpqV//09sEQKbD451HlPGpMke7EV1ykqHuWQUTc53WklXY63vvWteNvb3gZd12EYxmyTrh1OWl37oMqjR492LDzZtzOOOWkiDMNAJpOxGjAkSUIymRy57Kyf9/JJHblcbjhVh64h9M0vgpTyIJKEuafPYun5L4O5fVtLrtGpbZZPiZBluf2z0BQgGOUHDUYIYLrv6pqUw9qknb56Get3GjLKybjXkNFO99RhjHQ5eH2I3y8zTbrdutLECbuBQGCg2Wnj9k4QGxsSiYTVgFEsFkfiNNbve7nOlz+0otGolfseFNLe05BKBbCFZNOs29AR+Ol3QLdvs4zH+VBOoLVtljGGXC7neCPHYwkEKgUgOtfU8gJgkeFn5Nk/gxsFw5KeaBzvJio+zJGuHTNNunZIkgTDMCyylSRpoBHs4na8HtnjBDF6FBsbBtlGr2NwQ9qmaeLChQsghLge+AlqtkxGgCQB1Oj06pYGgWKxaBkKaZoGvbIPOXsJVFORoRICmo5YdQdSMAhj/SYEpCCCE44YhwWl9FDkkrtFxeJcO150BYBCoYBYLNYy/6wXJmnSMywODenyL7RSqSAYDDpO2O0Xo54ILDY2xGKxtsYGcRvjnJPGoSgKdnZ2YBgGNjY2Og7PHAQ0dQQIhYFaBQgGQZQ6jJv/XeeCl65Cqu0D1ETIaFhSqohMMFfPgcVjwPwCFtU69NgaapEEVE1r/ly5Akqpq+r7JA3cJ0G641ABiFGxuKqhlOKpp55CNBqFruttQ0a75Yr9SHfM4KRSrVaRyWSg6zqi0Si2trYmqjzg27A7Rokpj16NDcD4JwKLioSlpSXLA8ATROPQX/5GBB59BFAqMLdvh3lLhzlWhg45fwUAAYiEBb0CSakAJA45+zSk2j5oPAEmB4FIDCG1Cmn1GOaFTfD0RKPRaKu+iwW7bqN4DkPEOe37Ba6vyBYXF63voltUHAqFEAgE8OUvfxnhcBjPfe5zsbq66noS+N///d/jE5/4BAzDwJvf/Gb89m//then14aZJl1VVXHp0iWYpol0Og3DMNBoNFxfPF6Y54jELTY2EEKwsbHR8qTvZxtuj6EbREUCt6tkjCGfzw+9byewhSXoL3ltjxcxSOUMJKUCFo6BhaIwpAACtSLkerE5cYIxSPUyKBhYINQkXxuc/AvEPGOj0UClUmkzHeeEfKMV0qZhaoS4/25RMS+4njt3Do8//jg+8YlPQJZl3HHHHfjsZz871Oe3t7eHhx56CF/84hcRCoVwzz334Bd+4Rc8mbtmx0yTbjAYxNLSkjVhd39/f6qGU1JKrWnApmlidXV1oKW6W3vFXpFuN0WCYRgTIR6ptg+pVgaoAUmtg2oNSNQEDB0kIIPFFsB0FaRRg1TdB51Lwkwf72/bQp5xcbHp3csYg1EtQdq7CFasQ5HCuBJcgM5gRVmcjEfSZWfDjRjpDjI1QpIkS4r4kY98BE8++STm5+eRzWahKMrQ5/DII4/gxS9+MRIHE7Bf9apX4atf/Sr+8A//cKjtdcNMk64sy9aHxP89DiPzfmAYBmq1GhRFGWoaMD+OUaQX+lEkWO9lDFAqTZPx6Pz14ZX9olED0dWmoiDYY/nHKIhSBosvgOgNkNwVBDQVyw0VlJwAEssAIaCLKZBwBGAExtoJIBhpjvwxmo5jLBhuanf7ADENxHKXwYIBILKMqKYgGWa4jDlr3pmYnhCdvHqlJ4bBjRjpuvXSXVlZcR2RZjIZpFLX5+ml02k8+uijrrbZCTNNunZ46amrqupQ7xXH+EiShFOnTg19MXttmiOmOSRJ6qpIIIQ0SfDioyD7GQASWDgKduoOINRe9HM8/msXELj8WLNYJknQT/8C2MJyH2+Ugf0CoNTAQlGoRh3RS4+D3fJ8EJCD7QVgLm00CdfUIRd3QMxmFZyGoqCJ1b6Il+iN5gPl4JxYOAbSqEGOxBEOh1ty2nxpK45tV1XVU5/bGznSHRReeunaVSMjbcceyVbHhFFOjxiU7MTJEsvLy1haWsLOzo6r6MFtekGMlEWPhLW1tZ5pDkIpFmp5EEUB5pJNolOqIFefBDvhPKmWUgqZmgA1QAwdgcuPgUViTRLVVQSf+AG057+ys2KBSGDRBRClBKleahIqAyhtRtwMEujiCgilYOE42AFRStVi83f831odTKmCxfooAkoyANqM6AkBTBOMSKAgjp7NbV12B9MfGo1Gm6OXvWDXT3rCj3T7B7/XvbB1XFtbww9+8APr39lsFul02vV2nTDTpAu0LqG9NDLvdzumaSKbzVpm57yxQVVVT/LCbtMLhmFg78nHESxlsBGLIpzeBOZ7mMI0apAu/xzL9Swgs2ZaIBIHCYbBGtW2lzPGQE0T8s4FBDKXAQIwSGCMghEJBGhuo15pdosFOju40XgCRA42CbRWAgJhNAW+pEm0kTkwSW6JYolpgIk3LZFAqIF+PjkWjsFcTEPez4IRgAAwVk8AZaWPd7dOfxDRrfJub3kWCcePdAd7H+AN6f7iL/4iPvaxj6FQKCAajeKf/umf8N73vtf1dp0w86Qrgud03V5A/eSGxSLUwsKC540NbrdhGAaq1SporYSjUgORVApEkoH9DJgcABKrHd9LnnkcAKAFIwBtALV9IBAE0xpAast6Hc+pUUpByjmEsk+DRefACIFULYGoddBQFEwOgKgKaDAMExLIwTk53miEgEXnoN9yJ4Lf/ypIvYqgVoe59SxI8TikWhGMEJixBHCgWmChKKRqoUnGYACjYMH+UiAAQJePgMWTgKk3yT4UBSvV+36/Ezp5F4jpCSfDce5yNyvWipPcNw+MvEgvrK6u4o/+6I/wO7/zO9B1HW984xtx++23u96uE2aedO2RLuD+qd2N7OwuZZ3aYic1EVh8GIRCISxFg4gGAs05ZAAQCoPUy2CdSJdSEK0BFp2HEYg0c5yVfDNKXVoH29i2yFYcByRpDRAiAbLcjGzjCyAEkA0DMDSwYBjazS8EA0APbhbTNAHGEChlIClVIBIHW9kEJAlsPgntl18PUi5gb28Pa2urIIFQM0KnJmSlDHOumR+m8cWm2kGpAgQw51fAwt39NWwfNFi0XcLnNel1Sk+I7bKUUly5cqWtMSASibSYAHmNWY10vfTSvfvuu3H33Xd7sq1umHnStYPndd18EZ2Mc0qlEvb29hAOh7u6lAHeTQTudyS3qEhYMBs4nXsKRr0GNZECUkJuyjSBUBdCkqQmYWlNvTONL0AOhEBP3NbMkRLS4jdsfc7hKFpyo4YKurQGeuJ2wNCAYARB4Tvhn4309FkE9i6CShIINWHs70E7fjuIJIHIQZClNZjVhniigCQ3lQp8X0QCXUiBzq80XzND7b92w/H9/X2cOHGiJSoelUexiEl2drmJdKfdS9cJM0+6TsWOXp66vWBvbKhUKlbFf3Nzs6/GBkLcTwTup5BmVyRsLS1g7l//PzBqABSQ9zMgIbnpvgUAcgAsudZ9m0dOgzz9cwRNDURtgB65GSy+2EwlHDj18x/rPQsroKktSLkrzX+HY6BHb2lO7pXbLzNJkgBDQyD3NBCfh0wkMEoRrORBNQVmJG4Rj2GaIKYK0jABSQYjMmgw1E6uHpLtJHOrkiRBluWuJkBeexTPaqQ7ay3AwCEgXTu88k1w29ggbseNZKxbesFJkSA9+WMwQ236y+o6TMYQ2LkMdvqFzcgwHL+eauiESAzspjuQNR5D+PgJBMJR0ANTEjvZWiAE9Ohp0PSxptsXVy10g/U9HfjmShIgSQjKEpgkIZvNolqt4khyHiQoA3qjWYgjJhrheZCDVYAorJ/FyIejVyqp15TgRqPR5ubVyaPYjknndIchTz/SnRJ4IRsTc2vDNjYAo2vjtU9taJkoIRIdIQDYgcn34kD7ZkSCGQhjv1JDnKK/ZSwhTbLtF8Ew2MIySDnfVDcYGlgoimxdReFaBouLi9g+cQJBvdaMliNxgDEQ00A4EoHJrreQ8s+Jpz4kSbKOd9ZuzEGuNTE9wTXFdt8CJ49iscuOP9wnFekOuzL1I90JwUutLm9sqNVqIIRge3t77EbmIuzpBSePBPtFxza3QR7/PlArQ2IMMA2wW1508J8MpFYC9vcAMLCVrTaSFItky8vLqNVqKJVK0HXdulH5j+t8IiEwt58H6co5kEoBjWAMV+QFBDUdx48fb6pBGAPRCRijlkyMSDIkWYZEWnPE/E9+/PZZd2JapNdxT4KEvNpnJ9+CbukJPuCRKynGSWbDkqdPulOCYbS6uq4jk8mgXC5jeXkZm5ubeOKJJyYq+eLv5yTY99SGSBzsJb8Ocu4HYEodjfllxFePAgBItQjpR18HyoXma2PzMO+8G4jNW0tbkagSiYTVZk0pteadKYqCYrEITdMQCoVaiDgSiQxGxIEgaqvb2MMcKKVYXV1t7ZIjBDQUhaTVARwQayjW1m3WKarlBCz+yc+zufn+iXjUGDXRdzMB2t3dhWmayOfzUFUVkiS15YlHpZ5wU0hz6yw2Ccw86Q4yJ80OwzCQy+VQLBaRTCatxoZBt9MJXkS6mqbh/Pnz/U9tYAwEFLjlhTB0A0p5H3NqrSn9uvgzoJQHQgeqi1oJ0tl/g/m8X72ut3UokvFzcbphedTEIydVVS37RPHHKSLhXXzVahWpVKpjGocFQjDlAMCj3T59FfhxA61aTpGA+Q/QSsQ8bTFOTCK65iZAkiRhaWkJ0WjU6rKzpyfcehR3gptC2qQflMNg5knXjn7SC/yJns/nO0aOk2xu4IoEbiR+4sSJnnPdrr+Zy7aanWCMkSYRK/sgARlYXgWUelM6JslglQIMwwAxVASVCgijoKEIaHShJ7l10p2KRCzaJ3ICDoVCaDQa2N/fRyKRwPb2du9lYieyNTSQ2n6zJyK+2NtUB92JWNd15PN5aJrWJtkbdcFuknlVexqGd9nNz193KfbCo9gJbkjXi260cWP2jrgH+EgXJ4iNDfF4vGvkOK6RPXaIioTl5WXkcrn+CRdo+hcEQiAHwxllRkGoDtAgWHQeUq0EhCJguR0wSmEupkGoiWB9H0ySwaQAJLUGYhow48neCgSuleW7J8RxTIuu61AUBeVyGblcDowxy1gon88jEokgGo0O1omlqwhc/imgH5gTyUEYx2+7HskPAEIIyuUyMpmMNTqJEwFPuYy6YDftsi23HsWdvltfMjZj6KTTFSE2DvTT2ACMP73gpEjQdR25zB5IYQfQVbDYPDC31F2PSghYPAHUy5CMGihDsyVWDgDJFBhMQNfAlDqoFAA7/UJIfFbZQdOBZGhNz1pGYUabqgdCjSYpB8JWV5hUK0LSGwCRYMaTYB3Ijhw0VBSLRVBKrYnM3HSepyb29vZajGLEyNjpZpUK15qNF7z7TFMg5a6Abpzq6zPn4A86QgiOHj3adm2IhCAW7DgJ8+vNbZ54WiLdQdDJo1hMT5RKJTQazZFLTuoJP9KdcYhkKTY2yLI8lROBuykSJEKQru2BXM000wWMgq2dBBP8D5x3LIPNJWGE4ijkq0hJEmCogGmCLqRATB1saRN0frlpPqMfdHwxCslQwYjUJG9JRqCaA4gMJjXTFDQYBY0uWITL5CDAKORqHsbiquWHwMHztrVaDalUyjKcB2BV2MUlrEjElUoF2WzWKpjYlRNNza5ws/JOtT7BR97zB93CwkJP4hmmYMcj4l5EPO2Rbr/olJ4QZWxieoIxhmw2O3B6wo90J4ROkjHepcUYG2pIpdcje+ywKxLEIp51DI0qIqYChFcOoksKsncJbPlIc5puDxBCYDLACEQQqBebbl2EgEXiYJLcJHEALBAGDYQhaQoYNQEig4ZjAAiIocGMzDXTDIxB0hugodh1wiUEIHLTRNzUrdE5/Py4+9rJkyf7ukECgQDm5ubapE6ciGu1GvL5PHRdR4LoSCl1wDAhyzIC1Gg+SHqAMYZCoWDl9Ps9tm4YpmDH38eJeBYj3UHgZAJkGAaeeuopRCKRgTyK+Wfrk+6EIBrDcG/Ta9euIZ1Ot0RWg8CrSLdbqqO3IoGBHdgaArje7MAogN46U6B5cZ5/+hrSsSBiIRkkGERACkJmJiiufy40lgALRSDXimBSqJmOMLWDApYs7L/5B5PkAzVBk4yb/yGDMWblRqPR6HW9rQvIsox4PN7m2NVQFDTyYYT2d6FrKopyHEqhhohyraOErVarYXd3F8FgEMeOHRup5KgXEYt5Yl6k4vricXbYicZFk4B9Akwvj+JSqYR/+Zd/QSKRwPLysifTqkV8+MMfhizLuO+++zzbpohDQbpAs7Fhb28P9XrTku/UqVOunca8iHR59ZsrEnZ3dyHLspXX7AYSnYcpyWCaAhIINnOx88uOXgYcYmQFND8HTdOgKgpUvQZWq8MolaGDQJWqmIuGMR+SEQwEADkEc24FcqN8QLgyzHD8IIKVQeiB4kEKgMaXIFVyzd8xBhqJo66b2Lt6GYwxbG5uDlYAHBCSJCEWjwPxm4GtmxEEsNpFwhYKhaDrOgzDwOrqal+phFEdN9BKxFwxUS6XsbKyMvYOO06402Ke7uRRzB9GqqpiZ2cH3/zmN3H58mV86EMfQjKZxO///u/jzW9+s6tjqVQq+MAHPoCHH34Y9957r6ttdcOhIN2dnR0Ui0WsrKxgY2MD586dc73NbiqIfsGj5UGnNlgIBLEbX8dclEE2VLCldbC1k44vdbJb5PuIRCKIhMOQjGizaMYYGpRA0XUEDRXVqgpN1xEKyKBSAKYcQiQSRSQSRSAgQ2pUQUwNNBAGjTQN0FkwDHNxFcTUoZsUe/ki6kq+LW87TjhJ2EzTRCaTQalUsnSlu7u7yGazbVricRdlxFUBV9OIxyB213lZsLNjknrXfv0TeLdcIBDAC1/4QnzqU5/CpUuXkEgkcPbsWZw86XxfDIKvf/3rOH78ON7ylre43lY3HArSnZ+fRyqVaokeRump2y8opahWq6hWq+0eCX3ClEPQj5wE6bJEt7e8Ol3EEjUggYFJza88IlOEglFINIC4JINRBqproNRAXqHIF4poNHZaqtORiIyISRE8kJFRIiFfqlp52+2NjakRq/MiaiaTQSQSwfb2tqXFtpvEFAoFNBqNFrlbOBweXMI2AFRVtbrAOq0KxOiWw4uCnR2TLuANa3YjyzJOnTqFm2++2ZNjed3rXgcA+NjHPubJ9jrh0JCuSJBeeOq6ndrAR/gEAoH+xP9djqNTZ5Q9ldBtidgsmhErL8vYwesYAMogUwOyBEAOYj0ahhFIgYFYubVGo4FisWiRE18JRCIRHD16FJFIZGI3rh081WQYBtbX19sUK91MYjpJ2EQZm5tR7JRS5HI57O/vY2VlZeAHcT954l4FO6djmsWpEbIsD/U9nDlzBh/4wAdafnfy5En8zd/8zcDbGgaHgnRH4ak7jHrBrkg4cuQIcrmcqwqrE/kPQrbWewiBxImXMRAAlMigMiAbjSYpEwk00CwsSaYOGghbuTVOTrwQRSnF/Pw8TNPEM888AwAtS/VRRomdYJomcrkcSqXSwIQmmsQMK2HrtS8uX4xGozhx4oSr61PEoAU7AFbln2uoZ02q5uZB8epXvxqvfvWrh3qvFzgUpGvHuBsbOikSFEVxfRyiMmMYsuWgUhCEURB2IO4nEpgcADu4BCRqHgx8JAfqiFZwU6B6vd6mabVHifv7+9jd3QWAtrzpKExT+FQPsdPQq/zsIBK2Ti5svPFF0zTHyHsU6ETE/E/Ria1arYKQ5qpGjIbHEf26jXRnEYeCdL20d+ToR73QS5HgpexMbEUdqtJMCEw5DFgzcoVUgxwEd/BqRsEM9EAmJi6Hk8kk1tfXHavNTlGimJrgy3VKaUs07JaIeZESAI4cOdKz09ALdJSwObiw8WsgHo9jdXV1LMfXCXYy5WkYxhjS6TRkWbaIGBiPE9uN1gIMHBLStcML0u0VLfejSPCCdAkhqNfrCAaDCAQCrv1rgXZyY5IMk4WsdmBTCoJKMkr7+9YAzmGWw72W605E3Kv1V9wO7yabpGKCw+7CVqvVsLOzY0XKvDNvEBe2UaGfvPIoCnadjmXavHRHpc/lOJSkO0qzmq5TG/rcRj/gF/rc3Bz29/eRy+WsmzUWCSEWDiMYiULqNXqn4w4opHq5aXIeioCF4037RAD1eh17e81ZZ15Hj07L9V55Ux4Rc91msVi08uZedJN5CZ6GURTFGvEkoh8XtlFK2HhOPhwOd32QjqJg5wRK6dBTI7zKiY8bh4J03XjqdgK/aPjyp5+pDU7HxS/QfqMwe942kUggmUxaNyutlxEx6zCrVeglirzeNLThxNSXiThjkIvXIKl1AASkxmDMLaMRnrcIo18vAi/QK2/Kidg4mNMmyzKWlpYwNzc3VRI1/jBIJBKOaRigswubpmnW+TpJ2EQiHuY7EVcGfGU2KNwW7MRtiO/30wuHAF6kFwBYZFsqlbp6JHR7Py+E9VQX9CiSEUIQCQUR0hhYMN5sUGAUMdNAnkWg2DqwRBK2EzHRG03CPfBOoJSCFndxuZFDIrmEjSnQ24p5U13Xsbe3B0VRLKNz7l4lFrD4OfejXIx3RwAAIABJREFUJPAS9XrdyusP01osSthEpy7DMKAoilWc5E5d9mJdt1QMb8DY29vDwsKC5yuDfgt29qiYX9/DSjt90p0wnCJdt91kXDHw1FNPIRaL9Te1wQE8xdDNWapTJ5kdhB08SCwPhKZ4PjG3gEQyaW1PVVXrZuVELI7VicsMc2iW1HRNg6o2EJYlHD92HMEpGn8imuYkk0nHh4ForN2PksBL8NUPb37xcmUgFie5XA+AZZnYaDRQLpfRaDQ6Sth0Xcfu7i4Mw3C0rBwV+nViq9frUFXVOq9BCnamac6krSNwSEjXDjc5XVGRQCnFxsYGkgeENgx4iqHTvnp1krW8nshgXNJFJICaBzaMQhTrsHylNk+CSkPBKlUgQQEFEAkEwKJzkKckR8a/g729PUQika6mOZ2MtbvNcxMj4mGImEvUMpnMSKLHbug0cNIuYeNBRzQata7fSTZBANdJmBCCbDaLUqlkzcSzr/R6KSf8SHfC8Cqna1ckZLNZdw5ZjGF5IY4g1SGZBFQKHKQFhtTbSjKMyCICjdKBqbgEI5robmqOVk8CTdOQyWSwUw9jMyYjBIoak5CpGlALT7RExNFodCQRYjdwGZOu60NrWu1KAuD6g0dRFFeDNRuNhiVR29raanm4TQpiKkZRFOzs7CAWiyGRSMA0TW8HiboEV3VwPbtTtNqrYMd/55PuFGHQnG4nRUKhUBg+N8wYJKojFg6DMoYAMyGZFDpk0IPUxTB6WxYMQw+khCGN/b2fz4Xb39/H0lJr3jYO4ARaI2JFUbC/v+9phNjr+IbtJusHTmY49hWAUyqG/3Cj7XK53HWI5qRgmiay2SwqlUrHVEen8x2HhI0bD1Wr1Z6FvG554kajYWmLffXChCF2bvVLur0UCW5VEIRRGPxpzQAwEwwERJLc3bCEXPe47QHeLZfNZjE3N9dTJsSJSVySdooQxWKd26X6KLrJesGJiBljFimJxMRv8mQyaY2YmYZIS5yOMjc31zXV0el8Ry1hq1Qq2N3d7Xl83cCDIK4bf/aznz0Vq4xhcGhIV0SvnG4/Uxv4dlxJz9jBGHVVa1rTyRKI1H906ha1Wg17e3uQJGnoQkq3CNFOxPZiTi8THEVRrKhlXN1kvUAIsc6XO4EFg0EsLzcnUjQaDWSzWTQajYk3OfBCmaZpQ/sX9yNhy+fzaDQaNse53hI2wzAs1cnGxsbQ7c/cQ1dVVWxubiKdTk/VKmNQHBrStUe6TvpYHvXt7e31pUhwIz1jAAwGxKMRqJoGpVZFudaASq9LfkZlCsPzto1GA+l02nNn/U5E7FS8ciJi+1J40t1kdvTTsTXJJgdRE5xMJrG5uelpuqcfCVuxWGyZ5mA/X16M5g0sw66CeHAUi8Vwyy23zGx0K4KwTr6BMwZd11ui0p///Oe45ZZbLGtE0SNhbW2tr6ggk8mAMYbV1dW+j6OlSMYYZAIQMDAiQTdNKEqjhZwAtORLOREPAzEvurS0hKWlpYlWq0Ui5ufLq+rhcBiJRAKxWGzsutpuEJ3A0un0QHlDe4TIf7wk4kajgZ2dps/x2traSMcN9QNRwsa/Y8MwQAixGl6G0U7z8+RRfCqVmpprxC0ODekahtESlZ49exbb29swDMPSKvK2zH6/vFwuZ1XRe2Eou0Vb9MAvWr6ME3Om3W5Se942lUpNXZFBTHUkk0lL5qQoylQ0OIhOYGtra545gXUiYvtSvdfDllJqyaymcXVgl9HF4/GW8+5XOy1Gt/F4HMePH5/4g8VrHFrSPXfuHMLhsLXEHqYaXiwWUavVcOTIkY6vcWO32Gl73J1LJGMeLYlELMuyRWayLCOdTk9FXlQE7ybrluqwpybEm9RerPOaaCilKBQKKBQKY1sdiN+x+NOp7Zf7JUSjUayurk5dU4Cu69jZ2YFhGNjY2HBMAYhNLPxHVMZ84xvfQDgcxurqKlKpFI4ePXqoolsR0/XteQCuSNB1HXNzc9ja2hr6JupWSBP7zL0c7EcIaTMOF6MlRVFQqVTQaDSs9ywsLGBxcXGqIgKRzDp1k3E46Wr5TaooSkunmZ2U3BAxJ7NQKNS1AcNrdPqOnaZ08Otvfn4e8/PzLZ2Lk4aYW15aWsLy8nLH4+rUxMKJ+Ac/+AF+9KMfoVKpIBKJ4I477sAnP/nJqbqmvcKhiXR5RMUVCY1GA6lUaihjD45KpYJcLocTJ060/N7eSTaJ6Qj7+/sW0fIb1a4xnURzg9hNxiMXr8hM7LwSl632ZXovW8heTmCThmiKv7CwgFgsBk3TrFUAMB5z+G7gigIAWF9fH5ocxdztxsYGKKV47LHHkM1m8Zu/+ZsT9wAZBQ4N6eZyORSLRayuriIcDuOZZ57B/Pw8EonE0Nus1+vY2dnB9vY2AO9TCYNAzNvyQZz2Zaa9uYEv4cRcGifiURy32E22urra0qo6KtiJmBdyxPONRNptIROJBFZWVqbupuZkxhjD+vq641LdKTXBPYnFdMyopnQUCgXk83lXTSyMMeRyOeTzeczNzQ1lFDSrODSkSymFruvWv69evYpIJGLpK4dBo9HAM888g5tuumliZAsA1WoVmUwGsixjdXV1INmMk4JgmOiwG8Rut+XlZSwtLU10+duJiIHmMjeZTGJ+ft7VOXsN0dxnGDITPYn5A3cYc/huEJUT6+vrQ69gGo0Grl27Bl3XceTIEaysrEzN9zAOHFrS3d3dhSRJSKfTQ29T0zRcuHABW1tbCAaDllXjuKCqKjKZDFRVtSJHL/bvREqmabYRca9IidsGZjIZxONxpNPpqSvycB/ZarWKRCIBSZKs8+buXGJ0OAkiFnPLa2trnilPRCJ2c848Ki0Wi66UEzdydCvi0JAuLzZx8OkDa2trQ22L522vXbsGRVEsEbgXetpeEPW2y8vLSCaTI18GixIu/qd9ySo2c4jdZKurq0N1Q40SYjpmYWEBqVSqrVvMfs6clLyMDrvBNE3L82NYY/Fh9mmPiMV0jL1AyQ10gsGgqwcC386NGt2KOLSkWygUoCgKNjc3B96OU5HMLuPielqRkNy2gYrV4E5523GCR0riOQOwzKcXFxexsrIydZpg0QlsbW1toHRMp+hw0FVAN9iNxZ0eCONEpwIlV+8sLCwgmUz2bOt2Au/uy+fzWFhYwLFjx8amEplWHFrSLZVKKJVK2Nra6vv99rytRIAAKAAGCgITEvhgRy7xEQlJ7MfnbbL9qgd4xT8QCAyctx0HeAEll8tZ58WLdlxf2m8zx6jA24u9dgKzE7G4ChDPux8i1jTNatZZX1+fOl010CwgX716FaFQyFJODNLgwMGjW8MwcOTIka6SshsJh4Z0AVgu9EBnuZcdnRUJDCGYzRZeAAQEJggMdI5I7FMbeNsrd+Ry6rbiFX9N0zzN23oJcRyN/YEwaDPHKDCJ3HK3wpWTgoB3WhUKhakoNjqhl/2ivSgrNjjwc97d3UUkEkEsFkOhUPCjWwccKtLVNM0yvbHLvezoJf+SQBEExfUPh4GAQIUMpzHmndCt24pH58lkEqlUaurkS1zPWq/XB2qhtre+2lcBIjG5PWfuBMbz95PMLdvTMZyIQ6EQdF23VjGxWGzqCLdarWJnZwfxeByrq6t9PyBFx7lGo4E//uM/xrlz5xCLxfCsZz0LL3jBC/D2t799KiP6SeHQkq6qqrh8+TJuvvnmltf020nmRLoAgTYg6drBI558Po9QKARZlptTfiltyw9PKlcqdpN5pWe1u3IpiuKqmaMfJ7BJgxfKKpWKNZKm0WgfLjkqt7lBjrFerw89qQO4/n3kcjnUajWUy2WcO3cOzzzzDN7znvdgaWnJ4yOfXRwq0hWdxgzDwPnz53HLLbdY/z9YJ9n19AKHAQlml/RCL/C8bTAYRDqdblmmi8Y3/E97rjQajY684MJdtrzuJnOC3TDcno7p1MzhxglsXODG3U6Ro1NzwySImBfz5ufnkU6nh36wKoqCa9euwTRNHD161JU2/kbAoSVdSikef/xx3Hrrrda/B29uYJBBD/5GQDHcRSl2aqXT6b7ytvZcKY8MA4FAW97Qi7QEL/CMs5vMCfblquhCFgqFoKoqTNPE+vr6xI6xG0Rj8UHcyuxELNp+it+3F0TMnfdUVcX6+vrQKRkubSwUClhcXMTW1tZYc7cf//jHcebMGQDAS1/6UjzwwANj27cbTJeS3UNwIuKdSMAwnWTEVWRrGAZyuRzK5fLAS+BOpihim68406tbZNgN4jJ9Ggo8TgbpvMGhXC5bmtmrV69ORWMDh1tjcT7llxevuO2n3QAHQNtDt18iFqVqiUSiqwlRL/CaiWmaOHHixNjTB4888gi+/e1v40tf+hIIIbj33nvxta99Da94xSvGehzD4FCRLr/weM42EAjg0qVLHZUDo4J4A/IR3V5U00XrP+4pYR+dUygUWtp8Re8B+xQNseLfbXbaJCF2a508edKKpMTGhkqlYjXDjMN/wA7eHksI8azLihDSlYj5dA5OxOI5O9UDRPvFYUc3Ae3R7bFjxyZy3aRSKbzjHe+wroft7W1cu3Zt7McxDA5desEwDKtIxqvonJDEdlenLiu34A5bmUwGwWDQMt8ZN5y6jsTzlmUZ5XIZlFJXy8tRYhgnMCf1gJgr9bpAKa4SJjUh2MkIXyTicDgM0zRRLpexvLzsSisrRrdbW1tTUxy7dOkS3vSmN+Fzn/scjh8/PunD6YlDQ7qMMZw7dw4ALJ2gk0jfNE2LgMXcGY+Gh+0sazQayGQyE8+JdoJhGJYvraqqkCSpbULFOAp1vSCuErxQTjhpiMUVg5grHQR8/NM0GotzIq5UKsjn81YtY9BpFRxidJtIJCwvkmnA+fPn8da3vhX33XcfXv/610/6cPrCoSFdoNn6WyqVUK/Xrad9KBSycn/8x77MthesuKbUnid1uvm5aXqlUpla6ZKTD4EkSR2bGuzStXHph8UmjFHN/7KbhfNzF+eYdXvwihNu19bWpu7hCrTaL/I8PeCsmuj1AJrW6BYAfvjDH+L+++/HO9/5TrzmNa+Z9OH0jUNFuiIopajVaqjVaqhWq6jX69B13Zp0KrbqOuU7nTrLRPKORCKoVCpW182k++c7oVs3mR1iOsZJSyvmDb18sPBCWa1WQzqdxsLCwlgfXE4t3Xyyr3jOqqpaJvnT2MwCNJUy165d68t+0WlskKIoKJfL+NjHPoZ0Oo2trS3cfvvt+JVf+ZWpesDs7Ozg9a9/PR566CHceeedkz6cgXBoSdcJuq6jWq1aZMxzvOIyu1Pej3eW1et1VKvVlrRELBaz3jsty0yxm8wNkdklXLz10/4AGkY50I8T2KQgPoD4g5tSimAwaKWuJjGZo9vxcvtFN/llHiV/+tOfxhNPPIFnnnkG165dw/b2Nv7hH/5hBEc+HN73vvfhC1/4Qou3yj333IM3velNEzyq/nBDka4dPKIViZgXX5xaVn/4wx9iYWHBKpJFIpG2/LAoeeLvHedNOYpuMqd92NMxgxYo3TiBjQt2Y/FEItG2ErA3c4xiJdAL3FgmEAhgfX196HwrNwwqFotIJpM4evQogsEgisUi6vX6wI59PpxxQ5OuEyilUBQF1WrVSks8+eST+OxnP4uzZ8/ife97H170ohchFou1yc/EZarY0CAuz0c5Lod3vIVCoZF3k9nRyQbSnh8mhIzECcxr8FxmL2PxXisBuz+tlxDVE6urq67SMrVazRoTtLW1hWQy6emx9kK1WsU999yDT37yk12nbx8G+KTbAxcvXsRdd92FO++8E/feey9WVlZQr9ettITTMlsEb3W1d1g5pTOGvWE0TWtzKps07FIm/hDiq4jFxUUrLTMNy3MO0WlrEJMfEZ1MjnpppwcBfyiEw2Gsra0NndbqFN2OEz/5yU/w4IMP4uLFi/jqV7/qk+6NDtM0cenSpRa3Mp7v47k+nh9mjFltut3kSKKwn9+UjLG2qLDXjSRGOktLS1haWpoqAuPgTmCGYWBlZQUAHFcC9oh4nBCbRbiBvJf55W7a6UE8eSmlyGQyqFQqVnQ7LMTo9tixY66GuLrBu971Lrz+9a/HAw88gM985jM+6froD4yxlrSEOC7bnl6wk4pTVCjKt+w+CyJBxGKxqTV96ccJTDS9sU8wFh9Co2zxFY3Fx2kP6eTJ69TMwXPjXBsci8UGsl+0g0fz+/v7SCaT2NramooC8Mtf/vIbgnQn/0kfEhBCEIvFLBIEmjcVVzvU63WrRZfL1uxpiYWFhRafBbGbjvssBINBS+yeSqWGHhI4aohOYN1ajAkh1ufA84hioa5WqyGXyw0VFfaCqGddWloa+2SDQCCAubm5lnSQKOES23wJIaCUYmlpCclkcmjC5cTNGMP29vbEotsbGT7pjhCBQKCFSAG0pSVKpRIopW3ifF5wC4fDSCQSVnRS/v/bO/egKM/zDV/LLiBoOIlyFBFEINHQ1ko0tmNFYhEPxHrCJp0YNSNOPSWNB1K1rUlEY9UiKloP02IZjSEaMBiNkhltG7RgPdSmWkCRCooIsrAssAu7vz+c7/t94OKB3WUX/K4Zx5GR3XcZffbZ573v+6mro3fv3igUCu7fv09lZeUjqgFbdr3S+XJn81kdHBzENzABwUnY1NSEWq0Wl2KaUkw8DdIb/+DgYLvZbNA+b6Guro67d++KKWtCvoZ0P9/TuAml3a2XlxcDBgywi+72eUT+qXcxQnKY0NUJH6+FIqzVaqmurgYQu9pPP/2U6upqVq5cSWhoaJv/LFLVQG1tLXfv3m2Tw2uJhZlPg1Sq5uXl9cwpW09CqVSa7AqFQvzgwQMqKiqeuCZIukfN3Bt/ayJ1vgUEBLR582pv5qiurn7ETSiMooRCLQTyyN2t7ZGLro2Rfrzu168f8LCAabVaTp8+zYYNG1CpVMydO5fa2loaGxsf6Yalxai9rbmqqsqkrdmSl1XSJLCu7BqFrrD9SEaaPiZ97QqFQtziYKnkN0sjjV90d3cnJCTkkTcvaeynu7u7+H1SDXF9fT3JycncvHmTQYMG8eKLLzJy5EgxX7qnISwm6A7IF2l2zP79+2lsbGTevHkolUrRwCF0xFI3nbQQtx8vSG3N0ssqU9/3LP9wO5ME1tUYjUYaGhrEMCKlUklLS0sbK3hXRX4+CSEAXa/Xm70pWKPRcO3aNa5fv051dTVFRUUUFRWRlpZGVFSUBU9tWwwGg10qdh6HXHS7Ke3ddFqt9hHZ2uPGC+0lTMJa8fZuOlPdoKWTwKxFR+c0paMVCrGltNPPek7BDu3p6Ym3t3enn1fIsVCr1fTt25fAwEC77OgtgbS7PXPmDCdPnmTy5MlERUXZZVypgFx0exBGo1FUSwiFWFhLL3R2jxsvtE8da2xsbDMjdXFxEXWi1kwCswRSm7Gfn98Tz9mRdrqzF3VPi06n486dO2K2sTl2aGGjrxCmLoweuopjx46Rnp5OS0sLb731Fm+88YbVn7O1tZWPPvqIsrIyRo8eja+vL/Hx8VZ/XnOQi24PR8jRlY4lWlpaHon0MzVekM5IBcVFa2srKpWK3r17W93W3BksGSxu6k1Iqhow55JS2oWbuyZJuHQTgspt0d1WVlYye/Zsjhw5gpOTE4mJiWzZsoXBgwdb9HlaW1vb/LyvXbtGSkoKf/7zn7ly5Qq3bt2iqqqKQYMGMXbsWLuc9cpF9zmkubm5TSEWRgumsnSbm5spKSmhV69euLm50bdv30eMHO0/mltyG8ezIDisevXqhY+Pj8Wlc6YiIIWLuvaXm48btzQ3N3Pnzh3g6brwxyFsHVYoFAQHB5vlUDOHo0ePUlBQwPr16wHYsWMHRqORRYsWWfy5GhsbOXv2LDExMTQ2NvL6668DEBwcjJ+fHxqNhgcPHpCWltbl3f7T0DOHPTKPRdD/CoHUUjed0NFWVVVRUFBARkYGvr6+bN68GTc3N1QqlagGEJB+NFer1eLH+vbzYWvJ1qTyKmte6HWkGnjcslDpRR1AdXU1NTU1ZgfeS7tbb29vAgMDbRqLee/ePVF9A9C/f3+uXLlikceWdrf5+fls2LCBpqYmTp48yeLFi/n888/FGfYLL7zAl19+SUFBgV0WXJCLbof84Q9/QKlUsnjxYlsfxepI3XQCaWlppKenM2PGDKZNmyZ2D1I3ndSi27t3b1FLKrU1NzY2ijrS9hd85mbRGo1G1Go19+7d61BeZW2etCxU0F3r9Xrgod7Y29vbrFAiobt1cHAgLCzMZt2tFIPB8MhoytxPOoIyQalUotVq+c9//sM///lPtmzZgr+/P++//z7Hjh3j5z//OZWVlWzatAkfHx+uX7/O0qVLzX1JVkMuuu2or68nJSWF3Nxc5s+fb+vj2IyJEycyadIkBg0aJH5NcNMJv+rq6kTZWvuxhCkNrbQjrK2tNStjQQjRMRgMZm23tQbSTGVhxvzgwQM8PDzEAiLsLjP1c+sIe+tupfj6+lJYWCj+uaqqSrTDdxbhDfTKlSusWLECDw8Prl+/zrhx43BxcWHy5Mnk5ORw7tw5oqKiGDFiBE1NTaxZs8bu5rhS5JluO7744gtx48Lz0ul2FlNuuo5C4E1FOEozFoTfpWHopgqR0WgUP6KbewFlbRobG6moqMDZ2dnkjNlUyJHUTSgoGZydnWlsbBTXLg0cONAuulspwkVaVlYWLi4uJCYm8uGHH/Lyyy8/0+MIHXJraysKhYLk5GQcHR2ZMWMGwcHBbNiwAYVCIc6ON27cyM2bN1mxYgUhISHWeGkWRy66HZCWlgYgF91nRHDTSQuxTqcDaGNI6Ej1ILU1SwuRMBPWaDQ4OzubtSHB2hgMBqqqqlCr1fj6+j51Jm97N2FTUxPLli2jvLyc4OBghg4dyquvvkp8fLxdam+PHTvG7t270ev1TJ8+nXfeeeeZvr+9MgFg7dq15OTkkJeXh6enJ4WFhezevZvx48cza9YsysvLyc/PZ/r06ZZ8KVbluS26X331FSkpKW2+FhISwp/+9CdALrqWRK/Xd+ime9oQeMH55ujoiF6vt/qyzM4iKChcXMxfzV5XV8d///tfiouLqa6u5vr16xQXF5OWlsawYcMseGr7oa6ujv379+Ps7MyIESP44Q9/yPjx45k6dSoLFy5Eo9GQk5NDZmYmu3fv7pYxkM9t0X0SctG1HoL+t/2S0PYh8EqlkuzsbIKCgnjxxRfp378/SqWywwxeU2lrXVWIpRsnhO62s7S0tHD37l3q6+vp168fAQEBdjO7tSb5+fmkpKQQExNDfX09JSUl/PSnP2XEiBEkJCSQk5NDaGgopaWlXLt2jbi4OFsfuVPY32cUmR6PoIBwdnamb9++wP+76QTJWkFBATt37kStVvPBBx9gMBhQq9Vtiqo0g1cqW6uvr+fevXttHGVPu42jMwhqgj59+hASEmJWgRSiHFUqFUOGDLGLPAtrKHlMZSacPXuWn/3sZ8yZM4eWlhYuXLjAxo0biY+PZ8aMGcydO5czZ84QHBxMcHCwxc7S1chF18bYwjppjygUClF25uXlxaxZsxg7diyLFi1CpVLR0NBAdXW1STedMJaQytagraPMVPyh8HtnZWZSfbC/v3+nsoOlZ62srLSr7tZaSh7p7LampkbUK9+8eZPvf//74t8LCAigV69elJaW8tvf/lbUlXd35KLbAV0xVqisrGTr1q1trJOvvPKKxa2T3Q2VSsXf//53kxGRTwqBb696kAaCt48/rKur69DI8LixhNFoFLtbS+iDhVB2e+puAfLy8ggODubtt9+26OMqlUpqamr45JNPuH//PgDvv/8+QUFBZGdnM27cOFQqFV5eXmKOMsCSJUsseg5bIc90bUhXWid7KlLZmrAWSVhx096ea6qrlRoZpIljpoJuFAqFGL8obMYwJ81KeCyNRkP//v3x9/e3eXdrCkvcb0i728rKSpYsWUJMTAxTpkwhKyuL3Nxctm/fzq9+9StCQkIICgoiLy+P2NhYli1bZpHXYS/Ina4NsaZ18nnhcSHwQiGura3l3r174ixZGE24urq26XIF2q8GEmzNKpUKnU5Hnz59CAoKMkuyJu1uIyIizBpNmMuTlDzmIOhulUol1dXVotbY1dWVBQsWAA+L+cWLF/niiy/IyMggPz+fq1ev8vHHH/eo7F8BuejaEGtYJ2UeOplMrfaRjiWqqqrahMC3H0tIv1+n01FRUYFer8fNzQ29Xs+NGzdQqVRtuuGnsTXbY3c7YcIEJkyYYNHHvH37NkajkQEDBgBw+vRpduzYwcSJExk+fDgKhYLi4mJxlJaQkMA333xDnz59iIuL67bKhKdBLro2xBrWSRnTODo64uHhIeYjtA+Bb2hooKampo1szWg0cuDAAfz9/Zk8eXKbbcHSbRxNTU2P2JqlF3wKhUJcwyOsNbJ1d2ttdu3aRWFhIbm5uRQVFfHxxx8zefJk5s+fT1FREf379+fkyZMEBgbi5OTEl19+yejRo23+BtQVyEXXhrz66qukpaVRU1ODi4sLX3/9NR9++KGtj/VcIFVAeHt7A21D4PPz89m8eTMGg4GlS5dSV1cnaoFdXV3bjCkEpLbm+vp6qqqq+O6779i/fz8DBw4kODiYESNG8KMf/ciuNxuYg16vx9HRkY8++ogxY8Zw6NAhZs6cSVxcHCdOnODdd98lLCyMcePGcfToUZKSkqiqqiI2NpY5c+bY+vhdgnyRZmPMtU6ai0ajITExkV27dnVLd4+1SEpKws/PT7zEETpiIT/Y1MZlU266iooKPvvsM27evMmtW7e4desWw4YNIysryxYvq0u4c+cOR44c4fz581y9epXDhw/j7u7OypUriYyMZPny5eIF5o0bN3Bxcek2uQmWQC66zzGXL19m9erV3Lx5kxMnTshF9ykRQuAFtYSpEHgnJyfUajUNDQ34+vri5+eHg4MDarWapqafdZr+AAAJSklEQVQmfHx8bP0yrML9+/eZN28ecXFxTJo0ifXr16PVatm7dy/nz59n06ZNrFq1ilGjRtn6qDbD/rYJynQZhw8f5je/+Y08R35GhAD4oKAgIiIi+N73vkdkZCT+/v44OTmh0WioqKhAp9MRERFBQECAeMHm7u7epQX3woULTJ8+nYSEBN566y3Ky8st9titra2PfO327dt4e3uzcOFCBgwYQHp6OuXl5Rw8eJBRo0YRHR1NTk6Oxc7QHZE7XRliYmLIyMiQO10LYioxyxbExMSwc+dOIiIiyMrKIi8vj/T0dLMfV6q0OX78OAaDgcjISDw9PZkwYQIHDhxgyJAhwEOd744dO8jNzcXHx8esAPeegNzpyshYAXsouDqdjqVLlxIREQFAeHi4uJvNXBQKBTU1NSQlJXHixAnKyspYvHgx586dY9asWaxZswaNRkNNTQ1arZaxY8fi4uLy3BdckIuujEyPxcnJiYSEBOChsmL79u3ExsZ2+vGEXGSBI0eO8Morr7Bt2zZu376Nn58fYWFhzJkzB09PT9577z2mT5+Ot7c36enp+Pv7m/V6egqyZExGpgfwOFeZTqdj1apVtLS0iC6wZ+Hrr79m/PjxODk5UVlZyf/+9z8CAwNxcXHh4sWLzJw5k6ioKNLT0/n0009xc3Nj586d1NbW0tDQIBokZB4iF107QaPRcPbsWXx8fBg2bBhOTk493qG2fft2vvrqKwDGjBnDihUrbHyi7ktHrrKGhgYWLlyIh4cH6enpz2xdLisrY+PGjWg0Gvr168f69esJCwujrKwMo9FInz59WLx4MT/+8Y8ByM3NJTk5GQcHB7y8vHpMMpglkYuuHdDU1MTevXspKirCycmJ27dvs2DBAmJjYyksLMTNzU28lLAG33zzjdUeuyO+/fZb/va3v3H06FEUCgXz58/n1KlTvPbaa11+lp7M8uXLGThwIL/73e86lYQWGBjIokWL2Lt3L0FBQezbtw9/f3+ys7NZuXIlL730EufOnaOuro5Tp07h7u4ud7ZPQC66doBKpeLy5csMGTKE5ORksrOz+de//sW1a9fIz89Hq9USHh5OQEAA0dHRREVFodPpcHNz67bdcL9+/Vi1apVoKAgNDaWiosLGp+pZfPfdd+Tl5TF48GCmTp0KPAxV2rNnz1M/hoODA6+99hr5+flcunQJf39/WltbSUhI4NSpU2i1Wnx9fcnLyyMyMrJT44vnDVkyZidcvnyZXbt28cILLzBv3jzOnz/PmTNnWLZsGcOGDWP37t1kZGSwZcsW1Go1OTk5LFq0iIiICEpLS2ltbSUkJKRbFuDS0lJmz57NwYMHu/VGgJ5MUVERv/71r5k7d64YRrN582YiIyOJj4+nqampjSVapmPkTtcOOHLkCJ6enqSmppKVlcXChQvp27cvsbGxhIaGAhAVFUVgYCDh4eF89tln+Pn5ifOyY8eOUVJSQnJyMr179yY7OxsHBwdefvllXnrpJVu+tCdSVFTEggULWLFihVxw7ZjQ0FASExNJTU3Fw8ODmpoaTp06xZgxYwDkgvsMyEXXDujfvz9bt26ld+/eREdHU1hYiEKh4N///rcYjNLc3EyvXr3w8PCgtLSUgQMHikVXrVYzaNAgfHx8WLJkCYMHD0av13P06FGCgoJYt24dBoOBGzdu4OPjYzcW1AsXLrBkyRI++OADJk6caOvj2CWFhYWsX78evV5PQEAAGzduxN3dvcvP4eDgQFxcHKdPn2bp0qVMnDiRHTt2iE2BzNMjF107YPjw4SQmJpKRkUFNTQ0xMTH84Ac/YMeOHVy6dAkHBwf27NlDREQEzc3N1NbWMnz4cFQqFfX19dTV1Yn/+JOTk9FqtXh6evLmm28SGxvL8uXLuX//Pu+88w6DBg2ipqaGAwcO4OnpydWrVwkJCREjD7uKO3fu8Mtf/pKtW7c+1z78J5GcnEx6ejqDBw/m97//Pfv27eO9996zyVlcXV1ZvHgx5eXlZul9n3fkomsHuLi4MGPGDGbMmAH8v4V00qRJbN26lT59+tDU1ERoaChKpRKVSkVdXR0Aly5doqysjGnTpnH16lVSU1MJDQ3F1dWVy5cv4+7ujru7OxcuXAAgMzOThoYGdDodn3zyCRqNhhs3buDs7MymTZvw9fXtkte8b98+mpub2bBhg/i1xMREZs+e3SXPD5CamsrJkydRKBRMnz7d4rvALMHx48dxdHQUF1eGh4fb9DyRkZFERkba9AzdHbno2glCeIhSqRQtpFOnTmXq1KmUlJSQkpJCcHAwKpWKkSNHsmfPHs6fP09zczMKhQIPDw8yMzNxc3Nj1apVAPzxj39Eq9Xi7OxMcXEx0dHR4uNnZmZy4sQJcT58+vRpUlNTHxHYW4vVq1ezevXqLnkuU/zjH//g3Llz5OTk0NLSQnx8PGPGjLG7iEFHR0euX7/O22+/jUqlslmXK2M55KJrJ5jy6gsdb2VlJZWVleIIYfbs2cycOZOioiIePHjA/fv3xcSr7Oxs9u7di5eXF3/5y1+YMmUKBoOB0tJScd9UWVkZZWVlDB06lDVr1vDgwQPu3bvXZqtCd1RBPAvR0dFkZGSgUqmorKyktbXVpsHij3OUhYeH8+2333Lo0CHeffddDh06ZKNTylgCWTLWTSgvLycgIADouCjq9XoKCgo4f/48AOfOnWPKlCmMGjWKpKQk1q1bx8iRI6mvr2fu3LksX76c6OhoAG7cuIFOpyM0NNSshYvdjW3btrF//37i4uJISUmxqzeb5uZm/vrXv4rzU61Wy+jRo7l48aKNTyZjDnLR7cYYjUaxAHdULIQ9XocPH+YXv/iFuPV248aN6HQ63nzzTQDWrl3L2rVrCQsL67Lz2wuNjY0kJSURHx/PrFmzbH0ckdbWVn7yk5+Qnp7O0KFD+fzzzzl+/Dj79u2z9dFkzEAuuj0Mg8EgFuLH2T6rq6tJTU2luLiYpqYmJkyYwBtvvNFjd3e1p6SkBJ1OJ14KZWZmUlJSwtq1a218srYIkrHW1lZ8fHxYt25dl112ylgHueg+BwgdcUdFWKfTPbLfq6dz5swZtm3bxsGDB4GHO9GmTZsm64VlrI58kfYcYGr8YDQaMRgMODg4PHcFFx6mml25coXXX38dpVLJ+PHj5YIr0yXIna6MjIxMF/J/NSv6UyYdS/IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection='3d')\n",
    "ax.set_xlabel('square')\n",
    "ax.set_ylabel('bedrooms')\n",
    "ax.set_zlabel('price')\n",
    "ax.scatter3D(df['square'], df['bedrooms'], df['price'], c=df['price'], cmap='Reds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   square    47 non-null     float64\n",
      " 1   bedrooms  47 non-null     float64\n",
      " 2   price     47 non-null     float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 1.2 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据处理：添加 ones 列（x0）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "ones = pd.DataFrame({'ones': np.ones(len(df))})# ones是n行1列的数据框，表示x0恒为1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 1 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   ones    47 non-null     float64\n",
      "dtypes: float64(1)\n",
      "memory usage: 504.0 bytes\n"
     ]
    }
   ],
   "source": [
    "ones.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ones</th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.130010</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.475747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.504190</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>-0.084074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.502476</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.228626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.735723</td>\n",
       "      <td>-1.537767</td>\n",
       "      <td>-0.867025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.257476</td>\n",
       "      <td>1.090417</td>\n",
       "      <td>1.595389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ones    square  bedrooms     price\n",
       "0   1.0  0.130010 -0.223675  0.475747\n",
       "1   1.0 -0.504190 -0.223675 -0.084074\n",
       "2   1.0  0.502476 -0.223675  0.228626\n",
       "3   1.0 -0.735723 -1.537767 -0.867025\n",
       "4   1.0  1.257476  1.090417  1.595389"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([ones, df], axis=1)  # 根据列合并数据\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 4 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   ones      47 non-null     float64\n",
      " 1   square    47 non-null     float64\n",
      " 2   bedrooms  47 non-null     float64\n",
      " 3   price     47 non-null     float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 1.6 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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